A Storage Method of Ship Trajectory Data Based on ClickHouse Database

Yun Wen, Zhigang Lu, Liang Huang, Y. Wen, Jinfeng Zhang, C. Wan
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引用次数: 1

Abstract

At present, many maritime applications, such as ship traffic statistics, require fast spatiotemporal query of ship traj ectory data. The existing research is weak in supporting the trajectory spatiotemporal query, and can only realize the spatiotemporal query based on circular and rectangular regions. Moreover, complex spatial indexes and computer clusters are usually required to achieve efficient spatiotemporal query, which undoubtedly increases the storage cost. To solve above problems, this article designs the storage structure and partition strategy of ship trajectory data, and builds attributes multilevel index and H3 spatial index on ship traj ectory data based on ClickHouse database, which not only achieves spatiotemporal query based on the oval, round, and arbitrary polygon area, and improve the efficiency of the spatiotemporal query; At the same time, the data storage space is reduced, so that a common server can manage 10 billion ship trajectory data. The empirical study on a large number of data shows that the storage scheme designed in this paper not only enhances the ability of spatiotemporal query, improves the efficiency of data storage and spatiotemporal query, but also reduces the cost of data storage to a large extent.
基于ClickHouse数据库的船舶轨迹数据存储方法
目前,船舶交通统计等许多海事应用都需要对船舶轨迹数据进行快速的时空查询。现有研究对轨迹时空查询的支持较弱,只能实现基于圆形和矩形区域的时空查询。此外,为了实现高效的时空查询,通常需要复杂的空间索引和计算机集群,这无疑增加了存储成本。针对上述问题,本文设计了船舶轨迹数据的存储结构和分区策略,并基于ClickHouse数据库对船舶轨迹数据构建属性多级索引和H3空间索引,不仅实现了基于椭圆形、圆形和任意多边形区域的时空查询,提高了时空查询的效率;同时减少了数据存储空间,使一台普通服务器可以管理100亿个船舶轨迹数据。对大量数据的实证研究表明,本文设计的存储方案不仅增强了时空查询的能力,提高了数据存储和时空查询的效率,而且在很大程度上降低了数据存储的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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